计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2009年
32期
31-34
,共4页
双演化%模拟退火算法%文化算法%混合算法%测试函数
雙縯化%模擬退火算法%文化算法%混閤算法%測試函數
쌍연화%모의퇴화산법%문화산법%혼합산법%측시함수
dual evolution%simulating annealed algorithm%cultural algorithm%hybrid algorithm%test functions
提出一种基于模拟退火和文化粒子群的新型混合优化算法,该算法针对基本文化粒子群优化算法易陷入局部最优的缺点,将模拟退火引入文化算法框架中,作为知识空间的一个演化过程,通过模拟退火的概率突跳特性促使寻优过程跳出局部极值,保证了群体的多样性.最后通过8个标准测试函数的测试,仿真结果表明,该文算法是一种计算精度高、收敛速度快的混合优化算法.
提齣一種基于模擬退火和文化粒子群的新型混閤優化算法,該算法針對基本文化粒子群優化算法易陷入跼部最優的缺點,將模擬退火引入文化算法框架中,作為知識空間的一箇縯化過程,通過模擬退火的概率突跳特性促使尋優過程跳齣跼部極值,保證瞭群體的多樣性.最後通過8箇標準測試函數的測試,倣真結果錶明,該文算法是一種計算精度高、收斂速度快的混閤優化算法.
제출일충기우모의퇴화화문화입자군적신형혼합우화산법,해산법침대기본문화입자군우화산법역함입국부최우적결점,장모의퇴화인입문화산법광가중,작위지식공간적일개연화과정,통과모의퇴화적개솔돌도특성촉사심우과정도출국부겁치,보증료군체적다양성.최후통과8개표준측시함수적측시,방진결과표명,해문산법시일충계산정도고、수렴속도쾌적혼합우화산법.
A new hybrid optimization algorithm is presented,which is based on the combination of the simulated annealing and cultural-based particle swarm optimization.To overcome the shortcoming of cultural-based particle swarm optimization that it is easy to trap into local minimum,the simulated annealing algorithm is embedded in the cultural algorithm framework as an evolving course from the knowledge space,which respectively has its own population to evolve independently and parallel.The mechanism improves the population diversity.Finally by comparing the result of the example,it can be found that this proposed algorithm illustrates its higher computational accuracy,convergence rate.
